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WORK EXPERIENCE
  • •Leading the Implementation of On premise Infrastructure and deployments.
  • •Creating deployment guides and production builds for steady deployment on our production environment.
  • •Collaborating with Networks, Infrastructure, and Info Sec teams to ensure end to end delivery.
  • •Accomplishments: Pakistan's first ever SSK (Self Service Kiosk).
  • •Led Account Opening and Instant Debit Card Issuance Journey for New and Existing Customers.
  • •Core Responsibilities include: Architecture, System Design, Scalability and Fault Tolerance.
  • •Developed robust integration solutions within the middleware team to streamline system communication.
  • •Managed and secured APIs, ensuring safe and efficient exposure of endpoints to external users.
  • •Leveraged enterprise-grade tools like IBM App Connect and DataPower to implement and maintain high-level security standards.
  • •Built and Trained Neural Networks for Image Processing.
  • •Focused on unsupervised learning algorithms such as Principal Component Analysis (PCA) and different clustering techniques.
  • •Utilized data preprocessing techniques, including feature engineering, normalization, scaling, and regularization, to optimize model performance and achieve an effective bias-variance trade-off.
  • •Implemented various supervised ML algorithms, including linear and logistic regression, K-NN, SVM, Decision Trees and Random Forest.
  • •Enhanced machine learning model performance through effective data preprocessing and rigorous model validation, ensuring reliable and accurate predictions.
  • •Directed the development and launch of two e-commerce websites, driving their progress from concept to completion.
  • •Oversaw front-end stack implementation and backend operations.
  • •Ensured dynamic product listings and seamless user interaction, contributing to the functionality and performance of both platforms.
    • PROJECTS
  • •Developed an initial 1-layer neural network using TensorFlow for MNIST digit classification, achieving 85% accuracy.
  • •Enhanced the model with convolution layers, activation functions, and max-pooling, boosting accuracy to 90%.
  • •Optimized by adding Dropout and Batch Normalization, reducing overfitting and achieving a final accuracy of 97%.
    • PdM for Leased Vehicles, Kaggle | TensorFlow | Keras
  • •Engineered a preprocessing pipeline to clean and normalize sensor data for robust feature extraction.
  • •Developed an ensemble of ML models to predict machine failure and enhance fault classification.
  • •Solved a multi-class classification problem with advanced algorithms for precise fault diagnosis.
  • •Built an LSTM neural network for sequential data processing to effectively recognize and interpret sign language gestures.
  • •Designed a robust pipeline for preprocessing and feature extraction, significantly enhancing the system's recognition accuracy of 95% and performance.
  • •Processes invoice images to extract and provide information based on user queries.
  • •Uses Streamlit and Google AI to offer a straightforward interface for easy invoice analysis.
  • •Deploys effortlessly on Streamlit Cloud, making the app accessible for real-time use and interaction within the community.
    • EDUCATION
    ACHIEVEMENTS
  • •Conducted a workhop at our campus for enhancing problem solving skills and discussed the importance of a speacilaized resume.
  • •Solved 80+ problems on LeetCode with quality submissons beating 36% around the world.
  • •Crafted a plan for increasing the quality of existing Mock Interviews on our campus in order to prepare the trainees for onsite technical interviews.